System, Method and computer program product for evaluating admissions related data and compute comprehensible scores for further determination, evaluation, and conclusion of applicant-fit in a college or university system.

ABSTRACT

This patent discloses methods, systems, and a computer program product for remote analysis of multiple higher-education based factors and other applicant submitted data in undergraduate college admissions processes from a mobile (such as smartphones or tablets) or non-mobile device such as a computer, both of which utilize a data network to fine-tune decisions, along with user input data and previous behavior patterns in admissions processes. The methods and systems use primary and secondary data in real time to compute, evaluate and communicate the final result, an indicative scorecard to aid in further evaluation of the admissions committee regarding one or a set of applicants in the pool.

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BACKGROUND & FIELD OF THE INVENTION Field of the Invention

The System, Method and computer program serves to simplify research andprocesses in college admissions process for the Undergraduate Levelspecifically by a provision of a single-tool (as discussed in claims)evaluation software for quick computation of ‘understandable numericalboundaries and ranges’ and relevant processes on situations regardingindividual or group admissions in college. A prospective link and methodof communication via a data network of this computer program productwith previous years' admissions data and decisions on each applicant,along with general behavioural and miscellaneous data from third partieslike attitude towards admissions each year, public stigma's aboutadmissions each year, and number of common colleges applied to in thepast year would provide effective sources and databases for remotecomputations of each admissions profile to a college via manuallycontrolled devices and processes.

Background of the Invention

In the recent years, the importance of college and getting a degree fora future job or prospective opportunities has skyrocketed at anunprecedented rate which has caused a spike in the number of applicantsfor each college across the United States, and the world. For a reallysmall committee assigned to choose which increasingly smaller percent ofstudents with many different talents are offered a chance to attend thecollege has also been getting increasingly hard, given that humanbehaviour in essays for applications, human emotions and stories sharedin interviews, and the unlimited number of different accomplishments,experiences and circumstances is varied and complex, with increase inthe number of such entries due to educational importance.

College Admissions Committees have limited time to make tough decisionsfor filling in limited and (more or less) set number of seats with anincreasingly competitive pool of intelligent, vibrant, and overallexcellent students. Admissions processes now rely on subjectivemethodology of peer review and human reading of applicant profiles (thenumerical part such as grades and test scores, and non-numerical partssuch as extracurriculars and essays) to make final decision involvingmany layers of screening to arrive to a conclusion of the best-fit setof accepted applicants.

College Admissions Committees are many times unaware of the complexthought process of the applicant while creating the applicant profileand its dataset, along with other third party features affectingapplicants such as public opinion on colleges, rumors and so on. Thesedilemmas can be quickly and efficiently solved with this computationalcomputer program product to avoid confusion, provide additional data,and add layers of comprehensibility when making these decisions.

SUMMARY Brief Summary of the Invention

To bring more consistency to initial selection/filtration process,complex quantitative-algorithms and systems/technology can be developedto find best applicants for right courses in university.

Vast amounts of qualitative (including passions/interests/aptitude) andquantitative admissions data can be used to fine-tune outcomes throughNatural-Language-Processing, Machine-Learning and Predictive-Analytics;reducing human subjectivity and creating an indicative pre-evaluation‘scorecard’ (CASPER:Candidate-Acceptance-Scorecard-Predictive-Evaluation-Report) for bothAdmission-Committee and students. Universities can share a version ofthis scorecard (CASPER: ‘Friendly-Ghost’) for students to get predictivescores on acceptance probability.

The present invention incorporates a number of known technologies into anovel system for making admissions based determinations. Moreparticularly, embodiments of the present invention use a mobileapplication client (an “App”) and ability for the mobile applicationclient or non-mobile application client to perform search orcalculations and communicate with other admissions related news,sources, or related data existing over the internet over a datacommunications network.

These components are effectively accessible by the bundling algorithm,causing multiple such facets of specific code-language classesaccessible under one domain. With button and click functionalities,recording inputs and switching between components is made extremelysimple.

This bundle-functionality domain is accessible with and without internetapplication, in the form a web-computational tool online and in the formof a scientific application (downloadable) offline and send or receivedata over a data network to other users, systems or hardware.

The method of data-processing in the bundle-functionality will bedescribed in detail in the later sections. The method generally entailsthe way in which the computer program product will ‘flow’ the datathrough the program, giving the desired output.

The motive for transparency in the college admissions processes isfurthered by a sharing service of partial CASPER (comprehensive file)results (to protect the complete admissions status based intentions) forthe following user-end-efficiency protocols:

-   -   1. Withdrawing or continuing applications to the college in        question based on the shared data and its result in its full        context, to allow other applicants more time for consideration,        and more depth based evaluation.    -   2. Giving a similar report for related conglomerates of higher        education institutions.    -   3. Enabling knowledge about the stance of the applicant for this        college in particular, based on its personal importance        (tallying college interests in an applicant with applicant        evaluated scores and entries with college pre-set and chosen        weightages on certain aspects in the applicant file).

The invention's computer program product consists of software with 7components which can be further extended for providing more relatedfunctions and features:

-   -   1. A consolidating functionality which imports all data possible        related to admissions into the main F algorithm for the most        accurate decision process.    -   2. A set of separate cloud storage services for storage of        external, internal, suggestive, and semi-processed data all for        quick and easy identifier-based access at any invoking processes        in the start to finish run.    -   3. Functionalities to perform value-based crunching and        assignments to abstract phrases and datasets in context of        external information.    -   4. A set of functionalities to distribute, bucket, and assign        semi-processed values, and values for continuing the workflow        and making further evaluation easier and adhering to complex        mathematical functions.    -   5. Private databases of additional admissions material ready for        linkage and for a more comprehensive result.    -   6. A single dimensional fluid function service for pre-CASPER        values and initial crunching (in the Φ function, see FIG. 4.).    -   7. A multidimensional switch-amplified fluid function service        (the Δ to Σ function, see FIG. 4.), to synthesize human like        deterministic approaches to final CASPER based categorizing.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1: The inputs and sources of the software system leading to theactual CASPER report output, as well as the flow of information in andout of the system as a general scheme.

FIG. 2: The subtasks of the F algorithm, with its described intricaciesof flow of classification of inputs and it's separate processing to leadto a set of processed and compiled data.

FIG. 3: The complete module of the computer program product wherein afinal verdict is arrived at.

SPECIFICATIONS—DETAILED DESCRIPTION

A comprehensive set and subset of specific and delicate functionalitiesis paramount for the perfect workflow of the CASPER system. Data flowsfrom beginning to end, using various other sources, inputs, suggestionsalong the way to produce the ultimate desired result.

Referencing FIG. 1: The flowchart depicts the processing of data fromhuman input, to program generated output, along with general externalservers/linkages.

Referencing FIG. 1: The admissions committee clicks an ‘IMPORT’ buttonwhich imports the complete pool of admissions files (as digitized copiesin all supported file formats, like .pdf for essays, extracurriculars,test scores, report cards, letter of recommendations, .mp4 for musicrelated entries, .jpg/.png/.jpeg for visual entries in any field) intothe F algorithm in a linear fashion for evaluation by breakdowns of eachcomponent submitted for the final comprehensive CASPER score result.

Referencing FIG. 1: To supplement additional sources of data for a moreaccurate output in context of the full year's admissions cycle, pastyears admissions decisions data, already digitized, or made digital(since the applications before the 1990's or so were all paper) by ascan and Text Recognition System (A standard CTC Decoding Algorithm),and data from Social media, news, trusted college blogs/review/rankingpages will be inputted as an accessible object used after all of theadmissions profile data has been processed for adjustments to thePre-CASPER score.

Referencing FIG. 1: The data in addition to the admissions profile ofeach student is stored in separate end-to-end encrypted cloud serviceswith only 1 port of access: the special key (the admissions profilenumber) to utilize the existing data (in form of all supported fileformats which will be deciphered for image related data, and extractedto apply relevant data to the applicants profile by running the Base 1NLP feature).

Referencing FIG. 1: The final CASPER score result, comprising of acommon aptitude number, aptitude numbers specific to candidate selectedmajors, level of excellence in skills/traits that are preset by thecollege admissions committee (such as perseverance, computer-relatedskill, and so on) will be outputted. A common statistical analysis willthen be performed on these set of numbers per candidate, which wouldprovide quartiles, stacking by range of scores, and so on.

Referencing FIG. 2: The flowchart depicts the specifics of dataprocessing within the Γ algorithm, to give a final of the data report.

Referencing FIG. 2: The admission profile files are run through a parserseparating the test scores, examinations and grades files with all theother components. Each separate set of data files (containing its owndifferent components) are evaluated in a separate fashion first.

Referencing FIG. 2: The numerical component is all computed using aformula within the context of the applicants high-school and environment(town, any incidents leading to described performance, and so on) calledthe ‘Numerical Weight Computing Algorithm’ which uses main numbers suchas SAT/ACT scores, SAT Subject Test Scores, GPA's (weighted, unweighted)(or equivalents) and grades/percentages (of any sort with differentevaluated boundaries for each internationally situated curriculum),along with trends across years and subjects of the student's academicperformance in a complex mathematical formula with lesser weightedvariables such as additional factors that may have caused a boost/dip inperformance and so on. For example, a similar scoring system is the AI(academic index) system used by Ivy League Institutions in the US torecruit college athletes. This is then bucketed into a similar range ofscores decided by the admissions committee (for easy match and accesswhen evaluating this score separately and with the non-numericalcomponent's score). The required, recommended, and non-requiredsub-component here may/not have different weightages based on userinput.

Referencing FIG. 2: The non-numerical component has a Base 1 NLP, whichuses ML based enhancement to extract key information separately from theessays, letters of recommendations, extracurriculars, and awards. Astandard coreference resolution algorithm will be run on the extracteddata, and the keyset result will be processed through a Φ function, onewhich analyses the meaning, importance, depth, effort (of applicant),and difficulty of each related key set/subset of characters (or phrasesand sentences) and computes an array of comprehensive scores and rangesbased on the initial entries.

Referencing FIG. 2: This computed set of outputs is stored in a ‘resultcloud’ in a tabular fashion, where the tabulated numerals are eachassigned to a scorecard aspect that is part of the final result.

Referencing FIG. 3: The CASPER system is activated by the admissionscommittee by logging into their service page, which then leads to alinkage of all the files of the applicants, separated by Applicant ID's,which then further is fed into the Γ function leading to thecomprehensive CASPER score report.

Referencing FIG. 3: The computed reports are assigned to all applicantsback, and a snip-version of it is stored as an encrypted file (onlyaccessible on or after a committee set time before decisions), where thecommittee decides what part of the CASPER is to be shared with theapplicant (done through the ψ function which appropriately pairs thedata to the applicant and uses the preset filters from the committee toform the snipped file).

Referencing FIG. 3: The CASPER score distributer then assigns the set ofvalues in a 2-D array back to each applicant (as a 2-D matrix forms anaccessible table in each applicant object file). The CASPER score filesare then distributed and organized by peculiarity, similarity, datafalling in the same range, and so on into 3-Dimensional matrix buckets(to allow for matches in multiple criteria).

Referencing FIG. 3: This classified data (with appropriate keys at eachdatapoint to the appropriate applicant ID) is halted for a user input ofa number between and including 0 and 100 as the A function whichinterprets numerical ranges as toggles on a meter, amplifying a certainbehavior. In this case, the behavior is human interference in finalstacking of decisions of applicants, done by the Δ to Σ function. (Thisfunction will be described in further detail when referencing FIG. 4.).

Referencing FIG. 3: The final decisions assigned by the function arethen assigned appropriately as separate objects of Accept, Reject, andWaitlist decisions, along with any other nuance. The admit files arelinked by Applicant ID for appropriate and correct decisions to pop-upon decision day, along with the correctly sorted (by Ω function, andextracted by the ζ function) admission status package from the completefile-set of the Admissions Committee ready for remote user access.

Referencing FIG. 4: In the Φ functionality which is primarily used fornon-numerical component evaluation (see FIG. 2), uses a set of simplefunctions and storage modules for achieving a sub-result. A stored 3-Dmatrix of all the key strings (containing phrases, words, sentences andso on) (solely for quicker access) is separated according to similarmeaning and similar character containing datapoint strings using POS(Part of Speech) tagging, dependency parsing and NER (Named EntityRecognition) as tools to segregate outliers and non-outliers and theirpreviously described subcategories in buckets.

Referencing FIG. 4: These buckets are parsed through a mathematicalfunction assigning values to each passed datapoint, using a database of‘meaning-match’ strings, strings wherein similarity can be linked tocertain other values that are used as part of the function to compute acomplete value per matrix position. These value sets are then stored inan array of results for easier access. Correct locational identifiersare used throughout each process to link values back to the initial corephrases.

Referencing FIG. 4: In the Δ to Σ functionality, ξ being a number for 0to 100 is a parameter to a complex function with the nature f(x,y)mwhere mat(χ) is the complete multidimensional array (adapting to all thevarious n number of criteria computer per applicant in the CASPER report(full version)), these 2 parameters are used in the final discerningprocess of applicant status, where each real number (range) decides amultiplying factor and the choice of complex mathematical function(using a standard switch block) to be used in calculating a final number(which when compared and placed within 3 ranges, decides theadmit/reject/waitlist status) all of which is cumulatively stored aftersegregation in an encrypted temporary cloud of the ‘Result Pile’.

Further command from the committee (electronically leads to a separatedresult pile by status ready for the committee's viewing which is pairedwith the appropriate admissions package for all applicants).

Thus, the complete comprehensive complete computer program product canlead to significant advancements in quick and efficient collegeadmissions processes.

While specific ideas and embodiments have been illustrated anddescribed, numerous modifications come to mind without significantlydeparting from the spirit of the invention, and the scope of protectionis only limited by the scope of the accompanying claims.

While certain aspects of the disclosure are presented below in certainclaim forms, the inventor contemplates the various aspects of thedisclosure in any number of claim forms. For example, while only oneaspect of the disclosure is recited as a means-plus-function claim under35 U.S.C. .sctn.112, 6, other aspects may likewise be embodied as ameans-plus function claim, or in other forms, such as being embodied ina computer-readable medium. (Any claims intended to be treated under 35U.S.C. .sctn.112, 6 will begin with the words “means for”.) Accordingly,the applicant reserves the right to add additional claims after filingthe application to pursue such additional claim forms for other aspectsof the disclosure.

What is claimed is:
 1. A system for admissions predictions, evaluation,and sorting use comprising various processing algorithms to handle andcommunicate immense admissions related past and current data, mainlycomprising of multiple cloud based services to storeraw/semi-processed/processed data from all sources and mobile or nonmobile device or non mobile devices and/or another device and mobile ornon mobile device admissions file based search app client: and capableof receiving from a user or another device or system, a request tosearch or calculation for applicant file and applicant statusdeterminations, the request comprising a keyword or multiple keywords orselections or values; based on receiving the request: retrieving, fromstorage databases, Admissions and applicant status based numericalevaluation and deterministic analysis software engine comprising of; adata device comprising a plurality of database entries eachcorresponding to a respective admissions and applicant data relatedasset (such as non calculated or calculated values or data or metadataor digitized content), wherein each database entry comprises descriptivemetadata associated with the respective admissions and applicant datarelated asset (such as non calculated or calculated values or data ormetadata or digitized content); comparing, using control circuitry, thekeyword or multiple keywords or selections or values to the descriptivemetadata associated with each of the plurality of database entries;identifying, based on the comparing, a subset of the plurality ofdatabase entries that are associated with the descriptive metadata thatincludes the keyword or multiple keywords or selections or values, anapplication program interface to allow two way communication,interaction and data sharing between the computer program product andother relevant devices or systems, wherein the subset of the databaseentries comprises database entries for admissions and applicant datarelated determinations; and storing, in user or another device or systeminteraction metadata, the request; receiving, from the user or anotherdevice or system, a selection of the admissions and applicant datarelated asset (such as non calculated or calculated values or data ormetadata or digitized content); based on receiving the selection of theadmissions and applicant data related asset (such as non calculated orcalculated values or data or metadata or digitized content) storing, inuser or another device or system interaction metadata associated withthe request, an indication of the selection of the admissions andapplicant data related asset; receiving, from the user or another deviceor system; generating a list of admissions and applicant data relateddeterminations including the admissions and applicant data related asset(such as non calculated or calculated values or data or metadata ordigitized content) and where in the admissions and applicant datarelated search app client comprises: software to interact with andpresent data to a user via the user interface, software to interact withand present data to another device or system interface, software toretrieve data comprising at least one cloud based service reading fromthe another cloud based service associated with another device or systeminterface, software to send the retrieved data from mobile or non mobiledevice to the admissions and applicant data related determinationssearch or calculation or calculator engine via the data networkinterface, and wherein the system comprises: wherein the at least onecomputer processor of at least one of: the mobile or non-mobile deviceor non mobile device, the admissions and applicant data relateddeterminations search or calculation platform device, or the admissionsand applicant data related determinations platform, is configured to:calculate the admissions and applicant data associated attributes; andwherein the at least one processor is configured to send the admissionsand applicant data associated attributes of the device to the admissionsand applicant data related determinations search or deterministicevaluation or numero-text based analytical engine via the data networkinterface, and receive admissions and applicant data relateddeterminations data at the mobile device or non mobile device or nonmobile device for the device, from the admissions and applicant datarelated determinations search or calculation or calculator engine viathe data network interface, and display the admissions and applicantdata related determinations data on the user or another device or systeminterface of the mobile or non-mobile device or non mobile device;wherein the admissions and applicant data related determinations searchor deterministic evaluation or numero-text based analytical enginecomprises wherein the at least one computer processor of the admissionsand applicant data related determinations search or calculation platformdevice is configured to receive the derived or calculated data from theadmissions and applicant data related determinations search ordeterministic evaluation or numero-text based analytical app client viathe data network interface, send the derived or calculated data to theadmissions and applicant data related determinations process parametersdetermination subsystem computer program product via the data networkinterface, receive the admissions and applicant data related data fromthe admissions and applicant data related determinations processparameters determination subsystem via the data network interface, storethe derived or calculated data and the admissions and applicant datarelated determinations data in the admissions and applicant data relateddeterminations search or calculation database, and send the admissionsand applicant data related determinations data to the admissions andapplicant data related determinations search or deterministic evaluationor numero-text based analytical app client via the data networkinterface.
 2. The system according to claim 1 wherein: the admissionsand applicant data related determinations search or deterministicevaluation or numero-text based analytical app is configured to readdata from said another cloud service of said plurality of cloudservices; wherein the cloud services are encrypted by a known key in themain function of the software.
 3. The system according to claim 1wherein the admissions and applicant data related determinations searchor deterministic evaluation or numero-text based analytical enginecomprises wherein the at least one computer processor of the admissionsand applicant data related determinations search or calculation platformdevice is configured to calculate the admissions and applicant datarelated determinations from the received data.
 4. The system accordingto claim 1 wherein: the admissions and applicant data determinationssearch or deterministic evaluation or numero-text based analytical appclient further comprises wherein said at least one computer processor ofthe mobile device or non mobile device or non mobile device isconfigured to automatically communicate the admissions and applicantdata related determinations data to a pre-configured electronic address.5. The system according to claim 1 wherein: the admissions and applicantdata determinations search or deterministic evaluation or numero-textbased analytical app client further comprises wherein said at least onecomputer processor of the mobile device or non mobile device or nonmobile device is configured to display on the user or another device orsystem interface information regarding the admissions and applicantrelated determinations data.
 6. The system according to claim 1 wherein:the admissions and applicant related determinations search ordeterministic evaluation or numero-text based analytical app clientfurther comprises wherein said at least one computer processor of themobile device or non mobile device or non mobile device is configured toallow the user or another device or system to send the admissions andapplicant related determinations data to a user or another device orsystem-specified electronic address to monitor, manage or control thedevice.
 7. The system according to claim 1 wherein: the admissions andapplicant related determinations search or deterministic evaluation ornumero-text based analytical app client further comprises wherein saidat least one computer processor of the mobile device or non mobiledevice or non mobile device is configured to display on the user oranother device or system interface information regarding the admissionsand applicant related determinations data.
 8. The system according toclaim 1 wherein: complex mathematical and abstract computations withwords and processing of adjunct source based and text/raw numeral baseddata to provide comprehensive scorecards and understandable admissionsranges/strengths/weaknesses/probabilities/and future career or collegebased profitability (to the college and student) chances availablepurely by software systems, databases and data structures.
 9. Aadmissions and applicant related determinations client applicationcomputer program product embodied on a computer accessible mediumconfigured to execute, on at least one computer processor of a mobile ornon mobile device or non mobile device in communication or noncommunication with a admissions and applicant related determinationssearch or calculation platform over a communications network, remotelyobtaining admissions and applicant related determinations data,comprising: receiving, by the at least one computer processor, aninteraction from a user or another device or system by communicatingover data network; calculating, by the at least one computer processor,admissions and applicant related determinations or value; incorporatingan application program interface to allow two way communication,interaction and data sharing between the computer program product andother relevant devices or systems, wherein the at least one computerprocessor of the admissions and applicant related determinations searchor calculation platform device is configured to receive the derived orcalculated data from the admissions and applicant related determinationssearch or deterministic evaluation or numero-text based analytical appclient via the data network interface, send the derived or calculateddata to the admissions and applicant related determinations processparameters determination subsystem computer program product via the datanetwork interface, receive the admissions and applicant relateddeterminations data from the admissions and applicant relateddeterminations process parameters determination subsystem via the datanetwork interface, store the derived or calculated data and theadmissions and applicant related determinations data in the admissionsand applicant related determinations search or calculation database, andsend the admissions and applicant related determinations data to theadmissions and applicant related determinations search or deterministicevaluation or numero-text based analytical app client via the datanetwork interface; For responding, by the at least one computerprocessor, to the user or another device or system interaction byreading cloud based service readings from another cloud based service ofsaid plurality of cloud based services; wherein the cloud based servicesconnected to databases, or cloud based services connected to otheradmissions, and another cloud based service, other than a touchscreen, akeyboard, and a mouse; forming, by the at least one computer processor,a admissions and applicant related determinations search or calculationrequest by inserting, by the at least one computer processor, the cloudbased service readings from the plurality of cloud based services intothe admissions and applicant related determinations search orcalculation request; and sending, by the at least one computerprocessor, the admissions and applicant related determinations search orcalculation request, over the communications network, to the admissionsand applicant related determinations search or calculation platform; andreceiving, by the at least one computer processor, admissions andapplicant related determinations data, from the communications network,in response to the admissions and applicant related determinationssearch or calculation request; and wherein the method comprises:retrieving, by the at least one computer processor, data comprising theat least one cloud based service reading; and calculating, by the atleast one computer processor, admissions and applicant relateddeterminations or values.
 10. A method, comprising various processingalgorithms to handle and communicate immense admissions data, on amobile or non mobile device or non mobile devices and/or another device:capable of receiving from a user or another device or system, a requestto search or calculation for admissions and applicant relateddeterminations, the request comprising a keyword or multiple keywords orselections or values; based on receiving the request: retrieving, fromstorage circuitry, communicating with a data device comprising aplurality of database entries each corresponding to a respectiveadmissions and applicant related asset (such as non calculated orcalculated values or data or metadata or digitized content) wherein eachdatabase entry comprises descriptive metadata associated with therespective admissions and applicant related asset; comparing, usingcontrol circuitry, the keyword or multiple keywords or selections orvalue to the descriptive metadata associated with each of the pluralityof database entries; identifying, based on the comparing, a subset ofthe plurality of database entries that are associated with thedescriptive metadata that includes the keyword or multiple keywords orselections or values, wherein the subset of the database entriescomprises database entries for admissions and applicant relateddeterminations; and storing, in user or another device or systeminteraction metadata, the request; receiving, from the user or anotherdevice or system, a selection of the admissions and applicant relatedasset; based on receiving the selection of the admissions and applicantrelated asset (such as non calculated or calculated values or data ormetadata or digitized content) storing, in user or another device orsystem interaction metadata associated with the request, an indicationof the selection of the admissions and applicant related asset;receiving, from the user or another device or system; generating a listof admissions and applicant related determinations including theadmissions and applicant related asset (such as non calculated orcalculated values or data or metadata or digitized content) and whereinthe system comprises: wherein the at least one computer processor of atleast one of: the mobile or non-mobile device or non mobile device, theadmissions and applicant related determinations search or calculationplatform device, or the admissions and applicant related determinationsplatform, is configured to: calculate the admissions and applicantrelated or associated attributes; and wherein the at least one processoris configured to send the admissions and applicant related or associatedattributes of the device to the admissions and applicant relateddeterminations search or deterministic evaluation or numero-text basedanalytical engine via the data network interface, and receive admissionsand applicant related determinations data at the mobile device or nonmobile device or non mobile device for the device, from the admissionsand applicant related determinations search or deterministic evaluationor numero-text based analytical engine via the data network interface,and display the admissions and applicant related determinations data onthe user or another device or system interface of the mobile ornon-mobile device or non mobile device; wherein the admissions andapplicant related determinations search or deterministic evaluation ornumero-text based analytical engine comprises wherein the at least onecomputer processor of the admissions and applicant relateddeterminations search or calculation platform device is configured toreceive the derived or calculated data from the admissions and applicantrelated determinations search or deterministic evaluation or numero-textbased analytical app client via the data network interface, send thederived or calculated data to the admissions and applicant relateddeterminations process parameters determination subsystem computerprogram product via the data network interface, receive the admissionsand applicant related determinations data from the admissions andapplicant related determinations process parameters determinationsubsystem via the data network interface, store the derived orcalculated data and the admissions and applicant related determinationsdata in the admissions and applicant related determinations search orcalculation database, and send the admissions and applicant relateddeterminations data to the admissions and applicant relateddeterminations search or deterministic evaluation or numero-text basedanalytical app client via the data network interface.
 11. The methodaccording to claim 8 wherein: the admissions and applicant relateddeterminations search or deterministic evaluation or numero-text basedanalytical app is configured to read data from said another cloud basedservice of said plurality of cloud based services; wherein the cloudbased services connected to databases and 3rd party sources, or cloudbased services connected to other admissions.
 12. A set of methods inaccordance to claim 8 having detailed aspects wherein: i. The methodaccording to claim 8 wherein at least one computer processor of theadmissions and applicant related determinations search or calculationplatform device is configured to calculate the admissions and applicantrelated determinations from the received data. ii. The method accordingto claim 8 wherein: the admissions and applicant related determinationssearch or deterministic evaluation or numero-text based analytical appclient of the mobile device or non mobile device or non mobile device isconfigured to automatically communicate the admissions and applicantrelated determinations data to a pre-configured electronic address. iii.The method according to claim 8 wherein: the admissions and applicantrelated determinations search or deterministic evaluation or numero-textbased analytical app client of the mobile device or non mobile device ornon mobile device is configured to allow the user or another device orsystem to send the admissions and applicant related determinations datato a user or another device or system-specified electronic address tomonitor, manage or control the device. iv. The method according to claim8 wherein: the admissions and applicant related determinations search ordeterministic evaluation or numero-text based analytical app client ofthe mobile device or non mobile device or non mobile device isconfigured to display on the user or another device or system interfaceinformation regarding the admissions and applicant relateddeterminations data.
 13. Characteristics of the computer program productin the core function involving: i. A computer program product involving:multiple layers and dimensions of sorting, classifying, pre-processingand associating of initial data and suggestive data along with otherrelated inputs along the data flow of the software algorithmfunctionality. ii. A computer program product involving: complex flows(with switch-case, split function, multi-storage, statistical and NLP(enhanced with ML) based standard algorithms) and invoking of data alongthe activation and result display processes of the software system,wherein data is processed to provide various aptitudes of understandingthe applicant data in context of multiple fields.